Thanks for the helpful answer, @rsk97. Let me just add a bit: I discuss this briefly in my blog post under Classification as Natural Language Inference -> When Some Annotated Data is Available. In short, if you have a limited amount of labeled data, you can further fine-tune the pre-trained NLI model.
Mar 12, 2020 · BERT is the state-of-the-art method for transfer learning in NLP. For our demo, we have used the BERT-base uncased model as a base model trained by the HuggingFace with 110M parameters, 12 layers, , 768-hidden, and 12-heads. Datasets for NER. There are many datasets for finetuning the supervised BERT Model.
answer = question_answering_tokenizer.decode(index ed_tokens[torch.argmax(out.start_logits):torch.arg max(out.end_logits)+ 1]) assert answer == "puppeteer" # Or get the total loss which is the sum of the Cr ossEntropy loss for the start and end token positi ons (set model to train mode before if used for tr aining)
Bert for question answering: SQuAD. The SQuAD dataset is a benchmark problem for text comprehension and question answering models. There are two mainly used versions: There is SQuAD 1.0/1.1, which consists of ~100 000 questions related to snippets of ~500 Wikipedia articles containing the answer to the individual questions. The data is labeled ...
Aug 28, 2019 · A nother common application of NLP is Question Answering. We compared the results of the bert-base-uncased version of BERT with DistilBERT on the SQuAD 1.1 dataset. On the development set, BERT ...
🤗 Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, text generation, etc in 100+ languages. Its aim is to make cutting-edge NLP easier to use for everyone.
It's a hot day, and Bert is thirsty. Here is the value he places on each bottle of water: Value of 1st bottle: $7. Value of 2nd bottle: $5. Value of 3rd bottle: $3. Value of fourth bottle: $1. a. From this information, derive Bert's demand schedule. Graph his demand curve for bottled water. b.